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We provide expertise and experience in the full data science pipeline and help you with a data centric approach. For inquiries, write us at info@quantargo.com
Building predictive models: Using your in-house data we build and validate machine learning models, combined with external data sources and deployed at scale.
We transform your existing code base (yes - even Excel Sheets) and transform it into high-quality data products implemented as R- or Python packages. Easy to maintain, deploy and well documented.
We integrate a high-performance data science infrastructure within your company which makes most out of existing open-source tools like R- and Python, facilitates collaboration and is based on solid ground - either in the cloud (AWS, Azure, GCloud) or on-premises (Kubernetes).
Portfolio
Refactoring of an R-Shiny dashboard, implementation of new features and interactive forms. Implementation as an easy-to-maintain R-package and support for continuous integration and deployment within a docker container.
Refactoring of the Uniqa PIM market risk model codes to an R-package. Implementation of a unit-test-suite to ensure code quality and correctness of calculations.
Implementation of a continuous integration code pipeline for the market risk modeling packages. Setup and integration of the Jenkins build server and R package repositories for end users.
Workshops & Trainings
Quantargo offers custom training for companies and teams. Our big focus is on teaching data science infrastructure, modeling and best practices. For both Python and R.
Trainings consist of different modules which we combine to cover your team’s needs.